No description available

This project creates a web application for football analysis, leveraging deep learning and computer vision techniques. Using Streamlit, it detects and tracks players, goalkeepers, referees, and the ball in football videos. The application offers features like player recognition, team prediction, and position estimation on a tactical map

No description available

This project creates a web application for football analysis, leveraging deep learning and computer vision techniques. Using Streamlit, it detects and tracks players, goalkeepers, referees, and the ball in football videos. The application offers features like player recognition, team prediction, and position estimation on a tactical map

AI Football Analytics is a cutting-edge football tracking system that uses computer vision and deep learning to analyze player movements, ball possession, and in-game performance. By integrating YOLO for object detection, ByteTrack for tracking, and OpenCV for visualization, this project enables real-time football analytics with automated insights.

Coach Vision is an AI-based football analytics system that analyzes match videos to track players and the ball. Using computer vision and deep learning, it calculates metrics like player speed and distance covered and generates annotated videos with performance insights to help coaches and analysts evaluate gameplay.